Amazon MLS-C01 Exam - Topic 9 Question 52 Discussion

Actual exam question for Amazon's MLS-C01 exam

Question #: 52
Topic #: 9

An ecommerce company sends a weekly email newsletter to all of its customers. Management has hired a team of writers to create additional targeted content. A data scientist needs to identify five customer segments based on age, income, and location. The customers' current segmentation is unknown. The data scientist previously built an XGBoost model to predict the likelihood of a customer responding to an email based on age, income, and location.

Why does the XGBoost model NOT meet the current requirements, and how can this be fixed?

AThe XGBoost model provides a true/false binary output. Apply principal component analysis (PCA) with five feature dimensions to predict a segment.

BThe XGBoost model provides a true/false binary output. Increase the number of classes the XGBoost model predicts to five classes to predict a segment.

CThe XGBoost model is a supervised machine learning algorithm. Train a k-Nearest-Neighbors (kNN) model with K = 5 on the same dataset to predict a segment.

DThe XGBoost model is a supervised machine learning algorithm. Train a k-means model with K = 5 on the same dataset to predict a segment.

Show Suggested Answer

Suggested Answer: C

by Yuki at May 04, 2022, 12:17 AM

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Lemuel

3 months ago

kNN might not be the best choice for segmentation.

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Deane

3 months ago

PCA isn't really needed here, just classify directly.

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Lavonne

3 months ago

Wait, can k-means really work for this? Seems off.

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Jesus

4 months ago

I think option B makes sense, just adjust the classes!

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Dell

4 months ago

The XGBoost model only gives binary outputs.

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Karol

4 months ago

I feel like increasing the classes in XGBoost might not really solve the segmentation issue. We should probably look into clustering methods instead.

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Lamar

4 months ago

I practiced a similar question where we had to switch from a supervised to an unsupervised approach. I think k-means could be the right choice for this one.

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Maddie

4 months ago

I'm not entirely sure, but I think we might need to change the model type since we're looking for segments, not just a binary outcome.

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Jaleesa

5 months ago

I remember that XGBoost is mainly used for classification and regression, but it seems like we need clustering here instead.

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Gearldine

5 months ago

Hmm, this seems like a tricky one. I'll need to carefully read through the details and think about the legal responsibilities of the bank in this situation.

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Mari

5 months ago

I'm still a bit unsure about the Combine Shipments batch job. Does that automatically create and post the invoices, or just create them? I want to make sure I understand that option fully before selecting it.

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Josefa

5 months ago

We went over some practice questions, and I think picking is tied to order fulfillment, so A sounds right, but I'm a bit confused.

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Karol

5 months ago

This one seems pretty straightforward. I'm pretty confident the answer is CSRF.

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yak22

4 years ago

It is a clustering problem so it should be D because K-Mean allows to predict cluster/segments which are unknown in this case where in option C k-nearest is used for classification problem to predict class labels for individual data instances.

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